Xiang-Ke Niu1, Xue-Hui Chen1, Zhi-Fan Chen1, Lin Chen2, Jun Li3, Tao Peng1. 1. 1 Department of Radiology, Affiliated Hospital of Chengdu University, 82 2nd N Section of 2nd Ring Rd, Chengdu 610081, Sichuan, China. 2. 2 Department of Urology, Affiliated Hospital of Chengdu University, Chengdu, China. 3. 3 Department of General Surgery, Affiliated Hospital of Chengdu University, Chengdu, China.
Abstract
OBJECTIVE: The purpose of this study was to perform a systematic review and meta-analysis to estimate the diagnostic performance of biparametric MRI (bpMRI) for detection of prostate cancer (PCa). MATERIALS AND METHODS: Two independent reviewers performed a systematic review of the literature published from January 2000 to July 2017 by using predefined search terms. The standard of pathologic reference was established at prostatectomy or prostate biopsy. The numbers of true- and false-positive and true- and false-negative results were extracted. The Quality Assessment of Diagnostic Accuracy Studies tool was used to assess the quality of the selected studies. Statistical analysis included pooling of diagnostic accuracy, meta-regression, subgroup analysis, head-to-head comparison, and identification of publication bias. RESULTS: Thirty-three studies were used for general data pooling. The overall sensitivity was 0.81 (95% CI, 0.76-0.85), and overall specificity was 0.77 (95% CI, 0.69-0.84). As for clinically relevant PCa, bpMRI maintained high diagnostic value (AUC, 0.85; 95% CI, 0.82-0.88). There was no evidence of publication bias (p = 0.67). From head-to-head comparison for detection of PCa, multiparametric MRI (mpMRI) had significantly higher pooled sensitivity (0.85; 95% CI, 0.78-0.93) than did bpMRI (0.80; 95% CI, 0.71-0.90) (p = 0.01). However, the pooled specificity values were not significantly different (mpMRI, 0.77 [95% CI, 0.58-0.95]; bpMRI, 0.80 [95% CI, 0.64-0.96]; p = 0.82). CONCLUSION: The results of this meta-analysis suggest that bpMRI has high diagnostic accuracy in the detection of PCa and maintains a high detection rate for clinically relevant PCa. However, owing to high heterogeneity among the included studies, caution is needed in applying the results of the meta-analysis.
OBJECTIVE: The purpose of this study was to perform a systematic review and meta-analysis to estimate the diagnostic performance of biparametric MRI (bpMRI) for detection of prostate cancer (PCa). MATERIALS AND METHODS: Two independent reviewers performed a systematic review of the literature published from January 2000 to July 2017 by using predefined search terms. The standard of pathologic reference was established at prostatectomy or prostate biopsy. The numbers of true- and false-positive and true- and false-negative results were extracted. The Quality Assessment of Diagnostic Accuracy Studies tool was used to assess the quality of the selected studies. Statistical analysis included pooling of diagnostic accuracy, meta-regression, subgroup analysis, head-to-head comparison, and identification of publication bias. RESULTS: Thirty-three studies were used for general data pooling. The overall sensitivity was 0.81 (95% CI, 0.76-0.85), and overall specificity was 0.77 (95% CI, 0.69-0.84). As for clinically relevant PCa, bpMRI maintained high diagnostic value (AUC, 0.85; 95% CI, 0.82-0.88). There was no evidence of publication bias (p = 0.67). From head-to-head comparison for detection of PCa, multiparametric MRI (mpMRI) had significantly higher pooled sensitivity (0.85; 95% CI, 0.78-0.93) than did bpMRI (0.80; 95% CI, 0.71-0.90) (p = 0.01). However, the pooled specificity values were not significantly different (mpMRI, 0.77 [95% CI, 0.58-0.95]; bpMRI, 0.80 [95% CI, 0.64-0.96]; p = 0.82). CONCLUSION: The results of this meta-analysis suggest that bpMRI has high diagnostic accuracy in the detection of PCa and maintains a high detection rate for clinically relevant PCa. However, owing to high heterogeneity among the included studies, caution is needed in applying the results of the meta-analysis.
Entities:
Keywords:
MRI; Prostate Imaging Reporting and Data System; diagnosis; meta-analysis; prostate cancer
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